The goal of this research is to exploit the computational Capability of high performance and parallel computation by coupling it with the flexibility and interactivity of a visual prograrmning environment such as AVS, in order to facilitate the examination and prediction of biomolecular interactions. In the second year of this grant we have made significant progress by both developing and applying novel computational and visualization techniques to these goals: l) We have demonstrated AutoDock running in parallel on a DECServer 8400 with 96 processors and displaying results in AVS on a graphics workstation at SuperComputing 95. 2) We have incorporated a hybrid Genetic Algorithm(GA) into our AutoDock code, and have tested the implementation on a test suite of problems. Initial results indicate a significant performance enhancement. 3) We have developed a rapid molecular surface algorithm that enables interactive display of solvent excluded surfaces. We have installed a molecular surface server on the World Wide Web. 4) We have developed location based texture mapping for our spherical harmonic surfaces, in order to depict atomic level property detall on a coarsely triangulated surface. 5) We have begun to explore the use of rapid prototyping Laminated Object Manufacturing (LOM) to produce physical models for docking research. Molecular Docking in a parallel environment. Much of the work this year involved development of graphical interfaces to set-up, analyze, and visualize the flexible substrate docking runs. A number of tcl/TK panels were developed to set up the flexible torsions, calculate the atomic affinity grids and launch AutoDock runs on multiple processors. The grid calculations were modularized to run on multiple processors simultaneously. We have completed testing the AutoDock code on a test suite of five substrate docking problems. The results have been submitted for publication. AutoDock is available for distribution to the academic and industrial communities. Genetic Algorithm -- local/global search strategy in AutoDock. In collaboration with Professor Rik Belew and Scott Halliday, of UCSD Computer Science, we have incorporated a local/global search strategy into the AutoDock code as an alternative to the original simulated annealing. This code uses both cross-over and mutation for modifying the genotypes of the population -- the orientational, translational and torsional parameters of the substrate being docked. In addition it uses a mininuzer to optimize on a more local scale. This approach is easily parallelized. We are exploring the parameters to optimize the performance of the algorithm. In preliminary tests on test suite of substrate docking problems (above), we have found that the GA requires significantly fewer energy evaluations than simulated annealing to reach a sirnilarly converged state. Rapid computation of molecular surfaces. We have developed an efficient method of computing molecular surfaces which strictly follow the Richards definitions of solvent accessible and solvent excluded surfaces. These surfaces are important in protein docking and modeling to describe solvation and entropic effects of interaction. The surfaces are also key in visualizing proteins and their interactions. The solvent excluded surface forms the basis for the spherical har monic surface approximations that we use for visualization (see below) and for automated protein-protein docking. The code, MSMS, has been made available on the World Wide Web. In addition we have set up a "molecular surface server" on WWW that allows scientists to submit a set of molecular coordinates and atomic radii, and receive a VRML representation of the molecular surface for manipulation and viewing. (site: http://www.scripps.edu/pub/olson-web) Visualization of macromolecular assemblies using location based texture mapping. As our ability to compute larger biological systems progresses, we are faced with the problem of trying to comprehend these systems over multiple length scales. Visualization of large protein complexes and assemblies can tax even the highest performance workstations. Part of the problem is in the nature of the representation, and part in the sheer number of polygons required to represent the shape and properties of the systems involved. We have begun to develop an approach that capitalizes on some of the scaling properties of our spherical harmonic molecular surface approximations to reduce the number of triangles needed to represent these systems, and to take advantage of the texture mapping hardware that is appearing on even low-end computers. Because the spherical harmonic representation is globally analytic, we can describe a molecular surface by a user specifiable number of triangles. A coarsely triangulated surface cannot in itself represent atomic level detail, but with location based textures applied on the surface, these properties can be incorporated, without taxing the geometric processing. We have successfully tested this technique in the AVS environment displaying over lOO protein molecules simultaneously and still maintaining good interactive performance. Laminated Object Manufacturing rapid prototyping. We have begun to explore the use of "3-D Hardcopy" of protein surfaces (both solvent excluded and spherical harmonics surfaces), as an aid in the docking of proteins. We have produced a series of docking complexes representing a beta lactamase and a natural beta lactamase inhibitory protein as solvent excluded surfaces and as spherical harmonic approximations ranging from order 5 to order 20. These physical models have provided insight into the nature of the complementarity at various resolutions. Models have also been made of human tissue factor and domains of factor VHa. The interaction between these two molecules represents the initiation the blood coagulation pathway. Duncan, B.S., Macke, T.J., and Olson, A.J. Biomolecular visualization using AVS. Journal of Molecular Graphics 13, 271-282, 1995 Sanner, M.F., Olson, A.J. and Spehner J-C. Reduced Surface: An Efficient Way to Compute Molecular Surfaces. In Press. Biopolymers 38(3), 305-320, 1996 Duncan, B.S., and Olson, A.J. Texture mapping parametric molecular surfaces. Journal of Molecular Graphics, 13, 258-264, 1995.